Bin Wu

Research Scientist

Database and Storage Lab, Alibaba Cloud

Professional Summary

Bin Wu is a Research Scientist at the Database and Storage Lab at Alibaba Cloud. His work centers on driving innovation from Data+AI research to production, where he develops novel methods for top-tier conferences and deploys them at scale to solve critical business challenges. His current research focuses on Agentic RAG, NL2SQL, and AI Agents. Additionally, his research interests include theoretical computer science and large-scale database management systems.

Previously, he was a researcher at Huawei’s Noah’s Ark Lab. He received his Ph.D. in Computer Science from The Hong Kong University of Science and Technology (HKUST) in 2018, supervised by Prof. Ke Yi, and his bachelor’s degree from Fudan University in 2012. He is a recipient of the ACM SIGMOD Best Paper Award (2016) and the Research Highlight Award (2017).

Education

PhD in Computer Science

2012-09-01
2017-11-30

The Hong Kong University of Science and Technology (HKUST)

BS in Computer Science

2008-09-01
2012-06-30

Fudan University

Interests

Agentic RAG, NL2SQL, and AI Agents OLAP algorithms and systems Query optimization

Featured Publications

Anser: Adaptive Information Sharing Framework of AnalyticDB

liang-lin

• Aug 1, 2023 • 1 min read

CatSQL: Towards Real World Natural Language to SQL Applications

han-fu

• Feb 1, 2023 • 1 min read

AnalyticDB-V: A Hybrid Analytical Engine Towards Query Fusion for Structured and Unstructured Data

chuangxian-wei

• Aug 1, 2020 • 1 min read

Wander Join: Online Aggregation via Random Walks

feifei-li

• Jun 1, 2016 • 1 min read

Recent Publications

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Qingda Hu, Xinjun Jimmy Yang, Feifei Li, Junru Li, Ya Lin, Yuqi Zhou, Yicong Zhu, Junwei Zhang, Rongbiao Xie, Ling Zhou, Bin Wu, Wenchao Zhou (2026). PolarStore: High-Performance Data Compression for Large-Scale Cloud-Native Databases. 24th USENIX Conference on File and Storage Technologies (FAST 2026).

Pengyi Wang, Sibei Chen, Ju Fan, Bin Wu, Nan Tang, Jian Tan (2025). Andromeda: Debugging Database Performance Issues with Retrieval-Augmented Large Language Models. Companion of the 2025 International Conference on Management of Data (SIGMOD 2025).

Liang Lin, Yuhan Li, Bin Wu, Huijun Mai, Renjie Lou, Jian Tan, Feifei Li (2023). Anser: Adaptive Information Sharing Framework of AnalyticDB. Proceedings of the VLDB Endowment, 16(12), 2023.

Chunhui Shen, Qianyu Ouyang, Feibo Li, Zhipeng Liu, Longcheng Zhu, Yujie Zou, Qing Su, Tianhuan Yu, Yi Yi, Jianhong Hu, Bin Wu (2023). Lindorm TSDB: A Cloud-Native Time-Series Database for Large-Scale Monitoring Systems. Proceedings of the VLDB Endowment, 16(12), 2023.

Xiao He, Jian Tan, Bin Wu, Feifei Li, Xinping Zhang, Gaozhong Liang, Jinfeng Xu (2023). Active Sampling for Sparse Table by Bayesian Optimization with Adaptive Resolution. IEEE 39th International Conference on Data Engineering (ICDE 2023).

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